System methodology for building deterministic household objects without third party

ABSTRACT

In an anonymous matching system, a demand-side service platform (DSP) may select segments to populate a target audience. A data warehouse platform and a multichannel video programming distributor (MVPD) platform ingest address lists, eliminate personally identifiable information (PII) from the address lists, and process the de-identified addresses to generate deterministic unique anonymous household identifiers (UHIDs). Households may be selected, for example, at the DSP&#39;s direction, to form a query request without exposing the PII. In response to the query request, the MVPD platform determines a matching UHID and includes a matching household attribute, such as an IP address or the like, in a query response without exposing the PII.

BACKGROUND

Service providers include multichannel video programming distributors(MVPDs) that provide television, video, internet and other contentservices to subscribers or users. Demand-side platforms includeautomated advertisement campaign management processes that enableadvertisers to direct ad placements with MVPDs, for example, in realtime. It is increasingly challenging for service providers such as MVPDsto engage with DSPs and auxiliary services while maintaining security ofMVPD data, including subscriber data. In view of increasingly maliciousand pervasive attempts to breach privacy data, global privacy laws havebecome increasingly rigid, putting arduous requirements on serviceproviders to secure subscriber data. The security of personallyidentifiable information (PII) is essential as service providers areincreasingly regulated and a single data breach can cause potentiallycatastrophic embarrassment and damages.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated herein and form partof the specification, illustrate the present disclosure and, togetherwith the description, further serve to explain the principles of thedisclosure and to enable a person skilled in the relevant art to makeand use the disclosure.

FIG. 1 is a diagram of infrastructure of an anonymous matching system(AMS) according to an exemplary embodiment of the present disclosure;

FIG. 2 is a diagram of an exemplary embodiment of the anonymous matchingsystem (AMS) according to an exemplary embodiment of the presentdisclosure;

FIG. 3 is a flowchart showing an exemplary operational description togenerate deterministic de-identified unique household identifiers(UHIDs) according to an exemplary embodiment of the present disclosure;

FIG. 4A is a diagram of an exemplary embodiment of DW compiler serverthat can be implemented within the AMS according to an exemplaryembodiment of the present disclosure; and

FIG. 4B is a diagram of an exemplary embodiment of DW compiler serverthat can be implemented within the AMS according to an exemplaryembodiment of the present disclosure.

DETAILED DESCRIPTION

Overview

The systems and methods disclosed herein provide a demand-side platform(DSP) to target content, including advertisements for example, to MVPDsubscribers. The DSP directs a campaign toward selected audiencesegments based on one or more criteria, including demographics or othersegmentation data. Demographics, psychographics and segmentation dataprovides information on specific segments of the populace. Thisinformation may be nearly limitless and perpetually increasing. Forexample, such information may provide insights into consumers byinforming the decision maker about their age, gender, marital status,home ownership, geographic location, political affiliation, and thelike. Demographic information may include media content (e.g.,television content, internet content, or the like) that the populace hasviewed. Psychographic information may include information regarding howconsumers think and feel about issues, products, services, et. al. Thisis increasingly important to marketers.

In certain embodiments herein, the DSP may select, combine, or omit oneor more data elements or datasets to populate a target audience segmentfrom among the populace. The systems and methods enable a list of one ormore matched internet protocol (IP) addresses corresponding to membersof the target audience. Moreover, the embodiments described hereinenable interaction between two or more platforms, such as an audiencetargeting platform and the MVPD platform, without potentially exposingPII. With the sensitivity of nearly every enterprise, particularly MVPDsand service providers, to PII breaches, it is essential to be protectiveof how such data is used or captured. The systems and methods hereinenable the DSP, or other end user, to create the target audience in adeterministic manner but without exposing any PII. In the presentdisclosure, PII is not utilized in identifying members of the targetaudience. Instead, the members of the target audience are identifiedbased on households of interest instead of the specific members of thehouseholds of interest. Thus, an anonymous matching system describedherein returns IP addresses matched to households of interest to enablethe DSP, or the other end user, to address the households of interest ofthe target audience.

In certain embodiments herein, audience lists with information about thehouseholds of interest can include demographic, psychographic and othersegmentation data, physical address lists and potentially sensitive PII.In embodiments described in detail below, identifiers corresponding tothe households of interest can be de-identified, i.e. stripped of anyPII, to minimize the risk of abuse of such data, while still permittingdata warehouses and service providers to communicate information aboutthe households of interest, such as IP addresses to provide an example.The de-identified address lists may be converted into a cleansed andstandardized address list that can be used as a key for a uniquehousehold identifier. A unique household identifier (UHID) may begenerated to serve as a surrogate for the household for use within anaudience targeting platform (such as a data warehouse, for example). TheUHID may also be generated for use within an MVPD platform (or otherservice provider). For example, these UHIDs may be generated byperforming a one-way hash function on the de-identified address lists.Thus, a data warehouse may be able to identify and store hundreds ofmillions of household identifiers, with every household (not individual)stored in a de-identified manner. Thus, the UHIDs cannot be reversed toidentify the actual resident. Thereby, the target audience can be formedand reached without specifying the members of the target audiencethemselves and without exposing PII. Moreover, in embodiments herein, aDSP can be enabled to target content to every device and individual thatresides in a household based on that household's postal or physicaladdress.

Exemplary Anonymous Matching System (AMS)

FIG. 1 is a diagram of infrastructure of an anonymous matching system(AMS) according to an exemplary embodiment of the present disclosure. Insome embodiments, an anonymous matching system (AMS) 100 may interactwith content providers, advertisers, and the like, to execute deliveryof content, including advertisements, programming, products, servicesand the like.

As illustrated in FIG. 1, the AMS 100 includes a data warehouse (DW)platform 101 and a multichannel video programming distributor (MVPD)platform 102. In embodiments herein, a demand-side platform (DSP), 103can engage with the AMS 100 to direct the content to one or moretargeted households. As to be described in more detail below, the DSP103 selectively requests segmentation information of various householdshaving one or more characteristics, parameters, and/or attributes fromthe DW platform 101. These various households having the one or morecharacteristics, parameters, and/or attributes are to be included withinthe one or more targeted households. The DW platform 101 selectivelyrequests attribute information of the various households having one ormore characteristics, parameters, and/or attributes from the DW platform101 from the MVPD platform 102. The segmentation information and theattribute information are to be described in more detail below. Forexample, the DSP 103 can request segmentation information and/orattribute for households having tuned to channel five at 10:00 PM.

As illustrated in FIG. 1, the DW platform 101 maintains the segmentationinformation associated with one or more households. The segmentationinformation can include a household address as well as availabledemographic, socioeconomic and any other segmentation information. Forexample, the segmentation information can be related to a household andcan involve or include age, gender, marital status, home ownership,geographic location, political affiliation, consumer activity,television, internet or other viewership information, and the like,associated with any resident or other person associated with thehousehold address. As to be described in further detail below, the DWplatform 101 generates deterministic de-identified unique householdidentifiers (UHIDs) corresponding to the one or more households andstores and/or communicates the segmentation information using thesedeterministic de-identified UHIDs. In an exemplary embodiment, the DWplatform 101 stores the segmentation information as a listing which isindexed by deterministic de-identified UHIDs. As described above, the DWplatform 101 receives requests for segmentation information and/orattribute information of various households having the one or morecharacteristics, parameters, and/or attributes from the DSP 103. The DWplatform 101, in response to these requests, searches through thesegmentation information associated with the one or more households toidentify those households having the one or more characteristics,parameters, and/or attributes, for example, those households havingtuned to channel five at 10:00 PM. Thereafter, the DW platform 101 canprovide the deterministic de-identified UHIDs of those households havingthe one or more characteristics, parameters, and/or attributes to theDSP 103 and/or the MVPD platform 102.

As illustrated in FIG. 1, the MVPD platform 102 maintains the attributeinformation associated with one or more subscribers. Such attributeinformation can include, for example, an Internet Protocol (IP) addressof a subscriber at the household address. In the exemplary embodimentillustrated in FIG. 1, this attribute information is stored within theMVPD platform 102 and/or communicated by the MVPD platform 102anonymously. As to be described in further detail below, the MVPDplatform 102 generates deterministic de-identified UHIDs correspondingto the one or more subscribers and stores and/or communicates theattribute information using these deterministic de-identified UHIDs. Asdescribed above, the MVPD platform 102 receives deterministicde-identified UHIDs of those households having the one or morecharacteristics, parameters, and/or attributes from the DW platform 101.The MVPD platform 102, in response to receiving these deterministicde-identified UHIDs, identifies deterministic de-identified UHIDs of oneor more subscribers associated with the deterministic de-identifiedUHIDs of those households having the one or more characteristics,parameters, and/or attributes provided by the DW platform 101.Thereafter, the MVPD platform 102 searches through the attributeinformation to identify attribute information of the one or moresubscribers associated with the deterministic de-identified UHIDs ofthose households having the one or more characteristics, parameters,and/or attributes provided by the DW platform 101. For example, MVPDplatform 102 can identify attributes, for example IP addresses,associated with the respective households having tuned to channel fiveat 10:00 PM. Thereafter, the MVPD platform 102 can provide the attributeinformation of the one or more subscriber households to the DW platform101 and/or the DSP 103. In an exemplary embodiment, the attributeinformation of the one or more subscriber households can be provided tothe DSP 103 to allow the DSP 103 to direct the content to one or moretargeted households.

As described above, the DW platform 101 and the MVPD platform 102 storeand/or communicate the segmentation information and the attributeinformation, respectively, using deterministic de-identified UHIDs.These deterministic de-identified UHIDs allow the segmentationinformation and/or the attribute information to be stored and/orcommunicated anonymously without potentially exposing PII. For example,the deterministic de-identified UHIDs allow the segmentation informationto be communicated from the DW platform 101 to the MVPD platform 102and/or the DSP 103 without being able to identify the specifichouseholds having the one or more characteristics, parameters, and/orattributes provided by the DW platform 101. As another example, thedeterministic de-identified UHIDs allow the attribute information to becommunicated from the MVPD platform 102 to the DW platform 101 and/orthe DSPC 103 without being able to identify the specific subscribershaving the attribute information.

Exemplary Embodiment of the AMS

FIG. 2 is a diagram of an exemplary embodiment of the anonymous matchingsystem (AMS) according to an exemplary embodiment of the presentdisclosure. An anonymous matching system (AMS) 200 stores and/orcommunicates the segmentation information and the attribute information,respectively, as described above using deterministic de-identified UHIDsin a substantially similar manner as described above in FIG. 1. Thesedeterministic de-identified UHIDs allow the segmentation informationand/or the attribute information to be stored and/or communicatedanonymously without potentially exposing PII. In the exemplaryembodiment illustrated in FIG. 2, the AMS 200 includes the DSP 103, adata warehouse platform 201, and a multichannel video programmingdistributor (MVPD) platform 202. The data warehouse platform 201 and theMVPD platform 202 can represent exemplary embodiments of the DW platform101 and the MVPD platform 102 as described above in FIG. 1.

The DW platform 201 maintains the segmentation information associatedwith the one or more households in a substantially similar manner the DWplatform 201 as described above in FIG. 1. In the exemplary embodimentillustrated in FIG. 2, the DW platform 201 can include a memory device204 and a DW compiler server 210. As illustrated in FIG. 2, the memorydevice 204 stores the segmentation information, as described above inFIG. 1, associated with one or more households. This segmentationinformation is stored within the memory device 204 anonymously. As to bedescribed in further detail below, the DW compiler server 210 generatesdeterministic de-identified unique household identifiers (UHIDs)corresponding to the one or more households and stores and/orcommunicates the segmentation information using these deterministicde-identified UHIDs. In an exemplary embodiment, the memory device 204stores the segmentation information as a listing which is indexed bydeterministic de-identified UHIDs. The DW compiler server 210, inresponse to receiving a request for segmentation information, searchesthrough the segmentation information stored in the memory device 204 toidentify segmentation information of those households having one or morecharacteristics, parameters, and/or attributes identified in therequest. Thereafter, the DW compiler server 210 can provide thedeterministic de-identified UHIDs of those households having the one ormore characteristics, parameters, and/or attributes to the DSP 103and/or the MVPD platform 202.

The MVPD platform 202 maintains the attribute information associatedwith one or more subscribers in a substantially similar manner the MVPDplatform 102 as described above in FIG. 1. In the exemplary embodimentillustrated in FIG. 2, the MVPD platform 102 can include a memory device206 and a MVPD complier server 230. As illustrated in FIG. 2, the memorydevice 206 stores the attribute information, as described above in FIG.1, associated with one or more subscribers. This attribute informationis stored within the memory device 206 anonymously. As to be describedin further detail below, the MVPD complier server 230 generatesdeterministic de-identified UHIDs corresponding to the one or moresubscribers and stores and/or communicates the attribute informationusing these deterministic de-identified UHIDs. In an exemplaryembodiment, the memory device 206 stores the attribute informationassociated with the one or more subscribers as a listing which isindexed by deterministic de-identified UHIDs. As described above, theMVPD complier server 230 receives deterministic de-identified UHIDs ofthose households having the one or more characteristics, parameters,and/or attributes from the DW platform 201. The MVPD complier server230, in response to receiving a request for deterministic de-identifiedUHIDs, searches through the attribute information stored in the memorydevice 206 to identify deterministic de-identified UHIDs of one or moresubscribers associated with the deterministic de-identified UHIDs ofthose households having the one or more characteristics, parameters,and/or attributes provided by the DW platform 201. Thereafter, the DWcompiler server 210 can provide the attribute information of the one ormore subscriber households to the DSP 103 and/or the DW platform 201.

In some situations, the MVPD platform 202 can further include a queryserver 221 and/or a gateway server 220 to provide additional securitymeasures for protecting the attribute information is stored within thememory device 206. Although the query server 221 and/or the gatewayserver 220 are illustrated as being within the MVPD platform 202 in FIG.2, the query server 221 and/or the gateway server 220 can be in alocation remote from the MVPD complier server 230 which can be operatedby a third party, such as a cloud-based service. The gateway server 220operates as an intermediary between DW platform 201 and the MVPDplatform 202. In an exemplary embodiment, the gateway server 220provides control over the attribute information communicated to the DSP103 and/or the DW platform 201 to ensure the attribute information doesnot include any personally identifiable information (PII) that can beused to identify the specific subscribers having the attributeinformation communicated to the DSP 103 and/or the DW platform 201. Forexample, the gateway server 220 can scan the attribute information to becommunicated to the DSP 103 and/or the DW platform 201 for the PII. Inthis example, the gateway server 220 can send the MVPD complier server230 and/or an administrator of the MVPD platform 202 a notification thatthe attribute information includes the PII in response to detecting thePII within the attribute information. The query server 221 sends arequest or query to the MVPD complier server 230 for attributeinformation corresponding to the deterministic de-identified UHIDs ofthose households having the one or more characteristics, parameters,and/or attributes provided by the DW platform 201. In an exemplaryembodiment, the MVPD platform 202 can service multiple DSPs 103 and/ormultiple DW platforms 201 with each of the multiple DW platforms 201requesting various deterministic de-identified UHIDs of households. Inthe exemplary embodiment, the query server 221 can ensure the variousattribute information corresponding to the various deterministicde-identified UHIDs of households is routed to the proper DW platform201 from among the multiple DSPs 103 and/or multiple DW platforms 201.Thereby, the DSP 103 is enabled to target content to devices andindividuals that reside in the households corresponding to thedeterministic de-identified UHIDs and associated attribute information.

Exemplary Methods for Generating De-Identified Unique HouseholdIdentifiers (UHIDS)

FIG. 3 is a flowchart showing an exemplary operational description togenerate deterministic de-identified unique household identifiers(UHIDs) according to an exemplary embodiment of the present disclosure.The disclosure is not limited to this operational description. Rather,it will be apparent to ordinary persons skilled in the relevant art(s)that other operational control flows are within the scope and spirit ofthe present disclosure. The following discussion describes an exemplaryoperational control flow 300 for the MVPD platform 102, MVPD platform202, the DW platform 101, and/or the DW platform 201 to generatedeterministic de-identified UHIDs as described above in FIG. 1 and FIG.2. Unlike a conventional operation that may prepare a list of uniqueidentifiers based on PII, the exemplary operational control flow 300converts addresses, such as physical addresses, postal addresses, or thelike, into a standardized, de-identified, one-way hashed list of uniquehousehold identifiers as to be described in further detail below thatdoes not reveal the identity of individuals associated with a household.Thereby, the creation of a one-way hashed list of deterministic uniquehousehold identifiers can permit a platform to adhere to strict privacyrequirements, minimizing the risk of identity theft, privacy breaches,and the like.

At operation 301, the exemplary operational control flow 300 receives alist of addresses of the one or more households, such as a list ofphysical or postal addresses of the one or more households. This list ofaddresses of the one or more households can include street addresses ofthe one or more households and postal zip codes of the one or morehouseholds. In some situations, the list of physical addresses caninclude personally identifiable information (PII) identifying one ormore members of the one or more households, such as names of the one ormore members of the one or more households to provide an example. Inthis situation, the exemplary operational control flow 300 can removethe PII from the list of physical addresses of the one or morehouseholds at operation 301. For example, the exemplary operationalcontrol flow 300 can receive the list of physical addresses of the oneor more households that includes information, including a resident andresidential address “John Smith, 100 Main Street, 12345.” In thisexample, the exemplary operational control flow 300 can remove any PII,namely “John Smith.”

At operation 302, the exemplary operational control flow 300standardizes the list of physical addresses received in operation 301.Specifically, the exemplary operational control flow 300 can correctand/or standardize addresses from the list of physical addressesreceived in operation 301 to ensure uniformity among the addresses fromthe list of physical addresses received in operation 301. For example,the exemplary operational control flow 300 can standardizecapitalization and formatting, insert omitted information, correctspelling errors, correct abbreviations, and the like. As anotherexample, the exemplary operational control flow 300 can interact with athird-party API, such as an API provided by a postal service (e.g., theUnited States Postal Service) to standardize the list of physicaladdresses received in operation 301. From example above, the exemplaryoperational control flow 300 can standardize the physical address “100Main Street, 12345” to be “100 Main Street, Jonestown, AB 12345-6789” atoperation 302.

At operation 303, the exemplary operational control flow 300 generatesdeterministic de-identified anonymous UHIDs for the one or morehouseholds from the standardized list of physical addresses fromoperation 302. The exemplary operational control flow 300 can perform acryptographic function (e.g., generating a secure one-way hash algorithmsuch as SHA1) on the standardized list of physical addresses fromoperation 302 to generate the deterministic de-identified UHIDs for theone or more households. From the example above, the exemplaryoperational control flow 300 performs the cryptographic function on thestandardized address of be “100 Main Street, Jonestown, AB 12345-6789”to transform the standardized address to a unique household identifier,e.g., “A7C666FA7B16D3508E2 . . . .”

Exemplary Embodiment of the DW Compiler Server that can be Implementedwithin the AMS

FIG. 4A is a diagram of an exemplary embodiment of DW compiler serverthat can be implemented within the AMS according to an exemplaryembodiment of the present disclosure. In the exemplary embodimentillustrated in FIG. 4A, a DW compiler server 410 generates deterministicde-identified unique household identifiers (UHIDs) corresponding to theone or more households and stores the segmentation information usingthese deterministic de-identified UHIDs as described above. Asillustrated in FIG. 4A, the DW compiler server 410 includes a DWaudience ingest module 411, a DW staging module 412, an DW audienceidentifier (ID) creation module 413, and a memory storage 414. Forpurposes of this discussion, the term “module” shall be understood toinclude software, firmware, or hardware (such as one or more circuits,microchips, digital storage systems, processors, and/or devices), or anycombination thereof. In addition, it will be understood that each modulecan include one, or more than one, component within an actual device,and each component that forms a part of the described module canfunction either cooperatively or independently of any other componentforming a part of the module. Conversely, multiple modules describedherein can represent a single component within an actual device.Further, components within a module can be in a single device ordistributed among multiple devices in a wired or wireless manner,including cloud-based storage and processing. The DW compiler server410, as illustrated in FIG. 4A, can represent an exemplary embodiment ofthe DW compiler server 210 as described above in FIG. 2.

The DW audience ingest module 411 receives segmentation information,some which can potentially include including PII. For example, the DWaudience ingest module 411 receives can receive the segmentationinformation from at least one third party source. The PII may includeresidential address lists and can further include demographicinformation, socioeconomic information, interests, financial informationand other segmentation data. In the exemplary embodiment illustrated inFIG. 4A, the segmentation information can include a list of physicaladdresses of the one or more households, such as a list of physicaladdresses of the one or more households along with one or morecharacteristics, parameters, and/or attributes corresponding to thephysical addresses. This list of physical addresses of the one or morehouseholds can include street addresses of the one or more householdsand postal zip codes of the one or more households. In some situations,the list of physical addresses can include personally identifiableinformation (PII) identifying one or more members of the one or morehouseholds, such as names of the one or more members of the one or morehouseholds to provide an example. In this situation, the DW audienceingest module 411 removes the PII from the list of physical addresses ofthe one or more households. For example, the DW audience ingest module411 can receive the list of physical addresses of the one or morehouseholds that includes information, including a resident andresidential address “John Smith, 100 Main Street, 12345.” In thisexample, the DW audience ingest module 411 removes any PII, namely “JohnSmith.”

The DW staging module 412 standardizes the list of physical addressesreceived from the DW audience ingest module 411 to provide segmentationinformation for storage in the memory storage 414. Specifically, the DWstaging module 412 can correct and/or standardize addresses from thelist of physical addresses received from the DW audience ingest module411 to ensure uniformity among the addresses from the list of physicaladdresses received. For example, the DW staging module 412 canstandardize capitalization and formatting, insert omitted information,correct spelling errors, correct abbreviations, and the like. As anotherexample, the DW staging module 412 can interact with a third-party API,such as an API provided by a postal service (e.g., the United StatesPostal Service) to standardize the list of physical addresses receivedin operation 301. From example above, the DW staging module 412 canstandardize the physical address “100 Main Street, 12345” to be “100Main Street, Jonestown, AB 12345-6789”.

The DW audience ID creation module 413 generates deterministic,anonymous de-identified UHIDs for the one or more households from thestandardized list of physical addresses from the DW staging module 412.The DW audience ID creation module 413 can perform a cryptographicfunction (e.g., generating a secure one-way hash algorithm such as SHA1)on the standardized list of physical addresses from the DW stagingmodule 412 to generate the deterministic, anonymous de-identified UHIDsfor the one or more households. From the example above, the DW audienceID creation module 413 performs the cryptographic function on thestandardized address of be “100 Main Street, Jonestown, AB 12345-6789”to transform the standardized address to a unique household identifier,e.g., “A7C666FA7B16D3508E2 . . . .” In some embodiments, the DW audienceID creation module 413 can provide the deterministic, anonymousde-identified UHIDs for the one or more households as a first UHID listto memory storage 414 for storage. In these exemplary embodiments, theDW audience ID creation module 413 can thereafter retrieve the firstUHID list from the memory storage 414 and create a second UHID listbased thereon. For example, the DW audience ID creation module 413 canperform a second cryptographic function (e.g., generating a secure hashalgorithm) on the first UHID list to generate the second UHID list forthe one or more households.

The memory storage 414 stores the segmentation information from the DWstaging module 412 indexed by the deterministic de-identified uniquehousehold identifiers (UHIDs) for the one or more households from the DWaudience ID creation module 413.

Exemplary Embodiment of the MVPD Compiler Server that can be Implementedwithin the AMS

FIG. 4B is a diagram of an exemplary embodiment of DW compiler serverthat can be implemented within the AMS according to an exemplaryembodiment of the present disclosure. In the exemplary embodimentillustrated in FIG. 4B, a MVPD compiler server 430 generatesdeterministic, anonymous de-identified UHIDs corresponding to one ormore subscribers and stores and/or communicates the attributeinformation using these deterministic de-identified UHIDs. In anexemplary embodiment, the memory device 206 stores the attributeinformation associated with the one or more subscribers as a listingwhich is indexed by deterministic, anonymous de-identified UHIDs. TheMVPD compiler server 430, in response to receiving a request for theattribute information, searches through the attribute information toidentify attribute information of those households having one or morecharacteristics, parameters, and/or attributes identified in the requestas described above. As illustrated in FIG. 4B, the MVPD compiler server430 includes an MVPD ingest module 431, an MVPD staging module 432, anMVPD identifier (ID) creation module 433, and a memory storage 434. TheMVPD compiler server 430, as illustrated in FIG. 4B, can represent anexemplary embodiment of the MVPD complier server 230 as described abovein FIG. 2.

The MVPD ingest module 431 receives attribute information, some whichcan potentially include personally identifiable information (PII). Insome embodiments, the MVPD ingest module 431 can receive the attributeinformation from at least one third party source. In the exemplaryembodiment illustrated in FIG. 4B, the attribute information can includea list of physical addresses of the one or more households, such as alist of physical addresses of the one or more households along with oneor more non-PII attributes, for example Internet Protocol (IP)addresses, corresponding to the physical addresses. This list ofphysical addresses of the one or more households can include streetaddresses of the one or more households and postal zip codes of the oneor more households. In some situations, the list of physical addressescan include personally identifiable information (PII) identifying one ormore members of the one or more households, such as names of the one ormore members of the one or more households to provide an example. Inthis situation, the MVPD ingest module 431 can remove the PII, such assuch as the names of the one or more members of the one or morehouseholds, from the list of physical addresses of the one or morehouseholds. For example, the MVPD ingest module 431 can receive the listof physical addresses of the one or more households that includesinformation, including a resident and residential address “John Smith,100 Main Street, 12345.” In this example, the MVPD ingest module 431 canremove any PII, namely “John Smith.”

The MVPD staging module 432 standardizes the list of physical addressesreceived from the MVPD ingest module 431 to provide attributeinformation for storage in the data warehousing module 434.Specifically, the MVPD staging module 432 can correct and/or standardizeaddresses from the list of physical addresses received from the MVPDingest module 431 to ensure uniformity among the addresses from the listof physical addresses received. For example, the MVPD staging module 432can standardize capitalization and formatting, insert omittedinformation, correct spelling errors, correct abbreviations, and thelike. As another example, the MVPD staging module 432 can interact witha third-party API, such as an API provided by a postal service (e.g.,the United States Postal Service) to standardize the list of physicaladdresses received in operation 301. From example above, the MVPDstaging module 432 can standardize the physical address “100 MainStreet, 12345” to be “100 Main Street, Jonestown, AB 12345-6789”.

The MVPD ID creation module 433 generates deterministic, anonymousde-identified unique household identifiers (UHIDs) for the one or morehouseholds from the standardized list of physical addresses from theMVPD staging module 432. The MVPD ID creation module 433 can perform acryptographic function (e.g., generating a secure hash algorithm such asSHA1) on the standardized list of physical addresses from the MVPDstaging module 432 to generate the deterministic de-identified UHIDs forthe one or more households. From the example above, the MVPD ID creationmodule 433 performs the cryptographic function on the standardizedaddress of be “100 Main Street, Jonestown, AB 12345-6789” to transformthe standardized address to a unique household identifier, e.g.,“A7C666FA7B16D3508E2 . . . .”

The memory storage 434 stores the attribute information from the MVPDstaging module 432 indexed by the deterministic, anonymous de-identifiedunique household identifiers (UHIDs) for the one or more households fromthe MVPD ID creation module 433.

CONCLUSION

Although the embodiments of the disclosure described herein referspecifically, and by way of example, to cable modem systems, includingcable modem termination systems and cable modems, it will be readilyapparent to those skilled in the relevant art(s) that the disclosure isequally applicable to satellite systems, optical communication systems,telephone wire systems, home network systems, and/or any combinationthereof. It will be readily apparent to those skilled in the relevantart(s) that the disclosure is applicable to any point-to-multipointsystem.

The Detailed Description referred to accompanying figures to illustrateexemplary embodiments consistent with the disclosure. References in thedisclosure to “an exemplary embodiment” indicates that the exemplaryembodiment described can include a particular feature, structure, orcharacteristic, but every exemplary embodiment may not necessarilyinclude the particular feature, structure, or characteristic. Moreover,such phrases are not necessarily referring to the same exemplaryembodiment. Further, any feature, structure, or characteristic describedin connection with an exemplary embodiment can be included,independently or in any combination, with features, structures, orcharacteristics of other exemplary embodiments whether or not explicitlydescribed.

The Detailed Description is not meant to be limiting. Rather, the scopeof the disclosure is defined only in accordance with the followingclaims and their equivalents. It is to be appreciated that the DetailedDescription section, and not the Abstract section, is intended to beused to interpret the claims. The Abstract section can set forth one ormore, but not all exemplary embodiments, of the disclosure, and thus,are not intended to limit the disclosure and the following claims andtheir equivalents in any way.

The exemplary embodiments described within the disclosure have beenprovided for illustrative purposes and are not intended to be limiting.Other exemplary embodiments are possible, and modifications can be madeto the exemplary embodiments while remaining within the spirit and scopeof the disclosure. The disclosure has been described with the aid offunctional building blocks illustrating the implementation of specifiedfunctions and relationships thereof. The boundaries of these functionalbuilding blocks have been arbitrarily defined herein for the convenienceof the description. Alternate boundaries can be defined so long as thespecified functions and relationships thereof are appropriatelyperformed.

Embodiments of the disclosure can be implemented in hardware, firmware,software application, or any combination thereof. Embodiments of thedisclosure can also be implemented as instructions stored on amachine-readable medium, which can be read and executed by one or moreprocessors. A machine-readable medium can include any mechanism forstoring or transmitting information in a form readable by a machine(e.g., a computing circuitry). For example, a machine-readable mediumcan include non-transitory machine-readable mediums such as read onlymemory (ROM); random access memory (RAM); magnetic disk storage media;optical storage media; flash memory devices; cloud or third partystorage services; and others. As another example, the machine-readablemedium can include transitory machine-readable medium such aselectrical, optical, acoustical, or other forms of propagated signals(e.g., carrier waves, infrared signals, digital signals, etc.). Further,firmware, software application, routines, instructions can be describedherein as performing certain actions. However, it should be appreciatedthat such descriptions are merely for convenience and that such actionsin fact result from computing devices, processors, controllers, or otherdevices executing the firmware, software application, routines,instructions, etc.

The Detailed Description of the exemplary embodiments fully revealed thegeneral nature of the disclosure that others can, by applying knowledgeof those skilled in relevant art(s), readily modify and/or adapt forvarious applications such exemplary embodiments, without undueexperimentation, without departing from the spirit and scope of thedisclosure. Therefore, such adaptations and modifications are intendedto be within the meaning and plurality of equivalents of the exemplaryembodiments based upon the teaching and guidance presented herein. It isto be understood that the phraseology or terminology herein is for thepurpose of description and not of limitation, such that the terminologyor phraseology of the present specification is to be interpreted bythose skilled in relevant art(s) in light of the teachings herein.

What is claimed is:
 1. An anonymous matching system (AMS), comprising: adata warehouse platform, having a first server and a first memorydevice, configured to: store a plurality of segmentation informationassociated with a plurality of households indexed by a first pluralityof deterministic de-identified unique household identifiers (UHIDs)corresponding to the plurality of households, receive a request forsegmentation information for one or more households from among theplurality of households having one or more characteristics, parameters,and/or attributes, and provide a request for attribute informationcorresponding to one or more subscribers from among a plurality ofsubscribers that are associated with the one or more households, therequest including one or more first deterministic de-identified UHIDsfrom among the first plurality of deterministic de-identified UHIDscorresponding to the one or more households and not including personallyidentifiable information (PII) specifically identifying the one or morehouseholds; and a multichannel video programming distributor (MVPD)platform, having a second server and a second memory device, configuredto: store a plurality of attribute information associated with theplurality of subscribers indexed by a second plurality of deterministicde-identified UHIDs corresponding to the plurality of subscribers,identify one or more second deterministic de-identified UHIDs of the oneor more subscribers from among the second plurality of deterministicde-identified UHIDs that correspond to the one or more firstdeterministic de-identified UHIDs, and provide the attribute informationcorresponding to the one or more subscribers in response to the request,the attribute information including the one or more second deterministicde-identified UHIDs for the one or more subscribers and not includingpersonally identifiable information (PII) specifically identifying theone or more sub scribers.
 2. The AMS of claim 1, wherein the attributeinformation comprises: at least one internet protocol (IP) address. 3.The AMS of claim 1, wherein the data warehouse platform is furtherconfigured to generate the first plurality of deterministicde-identified UHIDs.
 4. The AMS of claim 3, wherein the data warehouseplatform is further configured to: standardize a plurality of householdaddresses associated with the plurality of households, and perform aone-way hash function on the standardized plurality of householdaddresses to generate the first plurality of deterministic de-identifiedUHIDs.
 5. The AMS of claim 1, wherein the MVPD platform is furtherconfigured to generate the second plurality of deterministicde-identified UHIDs.
 6. The AMS of claim 5, wherein the MVPD platform isconfigured to: standardize a plurality of household addresses associatedwith the plurality of subscribers, and perform a one-way hash functionon the standardized plurality of household addresses to generate thesecond plurality of deterministic de-identified UHIDs.
 7. The AMS ofclaim 1, wherein the data warehouse platform is configured to receivethe request for segmentation information from a demand-side platform. 8.The AMS of claim 1, wherein the data warehouse platform is furtherconfigured to: receive the plurality of segmentation information, atleast some of the plurality of segmentation information including PIIspecifically identifying households associated with the at least some ofthe plurality of segmentation information, and remove the PIIspecifically identifying households from the at least some of theplurality of segmentation information.
 9. The AMS of claim 1, whereinthe MVPD platform is further configured to: receive the plurality ofattribute information, at least some of the plurality of attributeinformation including PII specifically identifying subscribersassociated with the at least some of the plurality of attributeinformation; and remove the PII specifically identifying subscribersfrom the at least some of the plurality of attribute information.
 10. Adata warehouse (DW) system, comprising: a memory that stores a pluralityof segmentation information associated with a plurality of householdsindexed by a plurality of deterministic de-identified unique householdidentifiers (UHIDs) corresponding to the plurality of households; and aprocessor configured to execute instructions stored in the memory, theinstructions, when executed by the processor, configuring the processorto: receive a request for segmentation information for one or morehouseholds from among the plurality of households having one or morecharacteristics, parameters, and/or attributes, and provide a requestfor attribute information corresponding to one or more subscribers fromamong a plurality of subscribers that are associated with the one ormore households, the request including one or more first deterministicde-identified UHIDs from among the plurality of deterministicde-identified UHIDs corresponding to the one or more households and notincluding personally identifiable information (PII) specificallyidentifying the one or more households, and receive the attributeinformation corresponding to the one or more subscribers in response tothe request, the attribute information including one or more seconddeterministic de-identified UHIDs of the one or more subscribers fromamong the second plurality of deterministic de-identified UHIDs thatcorrespond to the one or more first deterministic de-identified UHIDsand not including personally identifiable information (PII) specificallyidentifying the one or more subscribers.
 11. The DW system of claim 10,wherein the attribute information comprises at least one internetprotocol (IP) address.
 12. The DW system of claim 10, wherein theinstructions, when executed by the processor, configure the processor toreceive the request for segmentation information from a demand-sideplatform.
 13. The DW system of claim 10, wherein the instructions, whenexecuted by the processor, further configure the processor to:standardize a plurality of household addresses associated with theplurality of households, and perform a hash function on the standardizedplurality of household addresses to generate the first plurality ofdeterministic de-identified UHIDs.
 14. The DW system of claim 10,wherein the instructions, when executed by the processor, furtherconfigure the processor to: receive the plurality of segmentationinformation, at least some of the plurality of segmentation informationincluding PII specifically identifying households associated with the atleast some of the plurality of segmentation information; and remove thePII specifically identifying households from the at least some of theplurality of segmentation information.
 15. A multichannel videoprogramming distributor (MVPD) system, comprising: a memory that storesa plurality of attribute information associated with a plurality ofsubscribers indexed by a first plurality of deterministic de-identifiedunique household identifiers (UHIDs) corresponding to the plurality ofsubscribers; and a processor configured to execute instructions storedin the memory, the instructions, when executed by the processor,configuring the processor to: receive a request for attributeinformation from among the plurality of attribute informationcorresponding to one or more subscribers from among a plurality ofsubscribers that are associated with one or more households, the requestincluding one or more second deterministic de-identified UHIDs fromamong a second plurality of deterministic de-identified UHIDscorresponding to the one or more households and not including personallyidentifiable information (PII) specifically identifying the one or morehouseholds, identify one or more first deterministic de-identified UHIDsof the one or more subscribers that correspond to the one or more seconddeterministic de-identified UHIDs from among the first plurality ofdeterministic de-identified UHIDs, and provide the attribute informationcorresponding to the one or more subscribers in response to the request,the attribute information including the one or more first deterministicde-identified UHIDs for the one or more subscribers and not includingpersonally identifiable information (PII) specifically identifying theone or more subscribers.
 16. The MVPD system of claim 15, wherein theinstructions, when executed by the processor, further configure theprocessor to: standardize a plurality of household addresses associatedwith the plurality of households, and perform a hash function on thestandardized plurality of household addresses to generate the firstplurality of deterministic de-identified UHIDs.
 17. The MVPD system ofclaim 16, wherein the instructions, when executed by the processor,further configure the processor to provide the attribute information toa query server.
 18. The MVPD system of claim 15, wherein theinstructions, when executed by the processor, further configure theprocessor to: receive the plurality of attribute information, at leastsome of the plurality of attribute information including PIIspecifically identifying subscribers associated with the at least someof the plurality of attribute information; and remove the PIIspecifically identifying subscribers from the at least some of theplurality of attribute information.
 19. The MVPD system of claim 15,wherein the instructions, when executed by the processor, furtherconfigure the processor to: scan the attribute information to beprovided for the PII, and generate a notification that the attributeinformation includes the PII in response to detecting the PII within theattribute information.